Under the framework of ghost imaging via sparsity constraints (GISC), we do numerical simulations on the influence of the speckle intensity distribution on image quality and study the relationship between the sampling number needed for information reconstruction and the speckle size and the target sparsity. Numerical simulation results show that, the speckle intensity distribution affects the imaging resolution. Gauss distribution is better than flat-topped distribution with the same speckle size, and the Gauss distribution is more suitable for practical application. In addition, when the speckle size is smaller than the resolution of the image, the sampling number required is only related to the image sparse degree, and it has nothing to do with the specific distribution of the image. When the speckle size exceeds the target resolution, to obtain the same image quality (based on the image with lower resolution), the sampling number needs to be inversely proportional to the square of the speckle diameter. The relationship between sampling number and the target sparsity is simulated and verified, while we give and verify the calculation formula of the sparse degree of the natural target with gray.